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operations is preferred, working knowledge of machine learning and artificial intelligence methods is highly desirable The successful candidate will demonstrate expertise in accelerator physics, accelerator
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science, including electronic structure methods molecular dynamics, and scientific machine learning. Experience with High-Performance Computing (HPC) systems and intelligent workflows. Demonstrated
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The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML) for applications in
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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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to the Lab’s broader effort in CH4 and CO2 utilization R&D. The role will require the individual to work with personnel that perform machine learning and molecular simulations and electrochemical device testing
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campus in Lemont, Illinois five days per week. Preferred Qualifications Proficiency in programming (e.g., Python) for advanced data analysis, machine learning, and computer vision to accelerate insights